PSO-PID Control Algorithm Implementation in MATLAB

MATLAB code implementation for PSO-PID control system

PSO-PID control is an optimization algorithm that combines Particle Swarm Optimization (PSO) with Proportional-Integral-Derivative (PID) control. This hybrid approach helps optimize control system performance by improving response speed and stability. In MATLAB implementation, the PSO algorithm iteratively adjusts PID parameters (Kp, Ki, Kd) to minimize a predefined cost function, typically using performance metrics like ISE (Integral of Squared Error) or IAE (Integral of Absolute Error). The code typically includes functions for particle initialization, velocity update using inertia weight and cognitive/social parameters, fitness evaluation through system simulation, and global best tracking. Key MATLAB functions involved may include ode45 for system simulation, pidtune for baseline PID parameters, and custom PSO loops with position update equations. By implementing PSO-PID control, engineers can automatically tune PID parameters based on specific system responses and performance objectives, achieving optimal control performance while addressing various control requirements through systematic parameter optimization.